Alan A. Stocker

Analog VLSI Circuits for the Perception of Visual Motion (eBook, PDF)

• Format: PDF

Produktbeschreibung

Although it is now possible to integrate many millions of transistors on a single chip, traditional digital circuit technology is now reaching its limits, facing problems of cost and technical efficiency when scaled down to ever-smaller feature sizes. The analysis of biological neural systems, especially for visual processing, has allowed engineers to better understand how complex networks can effectively process large amounts of information, whilst dealing with difficult computational challenges. Analog and parallel processing are key characteristics of biological neural networks. Analog VLSI circuits using the same features can therefore be developed to emulate brain-style processing. Using standard CMOS technology, they can be cheaply manufactured, permitting efficient industrial and consumer applications in robotics and mobile electronics. This book explores the theory, design and implementation of analog VLSI circuits, inspired by visual motion processing in biological neural networks. Using a novel approach pioneered by the author himself, Stocker explains in detail the construction of a series of electronic chips, providing the reader with a valuable practical insight into the technology. Analog VLSI Circuits for the Perception of Visual Motion: * analyses the computational problems in visual motion perception; * examines the issue of optimization in analog networks through high level processes such as motion segmentation and selective attention; * demonstrates network implementation in analog VLSI CMOS technology to provide computationally efficient devices; * sets out measurements of final hardware implementation; * illustrates the similarities of the presented circuits with the human visual motion perception system; * includes an accompanying website with video clips of circuits under real-time visual conditions and additional supplementary material. With a complete review of all existing neuromorphic analog VLSI systems for visual motion sensing, Analog VLSI Circuits for the Perception of Visual Motion is a unique reference for advanced students in electrical engineering, artificial intelligence, robotics and computational neuroscience. It will also be useful for researchers, professionals, and electronics engineers working in the field.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 242
• Erscheinungstermin: 30. März 2006
• Englisch
• ISBN-13: 9780470034880
• Artikelnr.: 37290182

Autorenporträt

Alan A. Stocker is the author of Analog VLSI Circuits for the Perception of Visual Motion, published by Wiley.

Inhaltsangabe

Foreword. Preface. 1 Introduction. 1.1 Artificial Autonomous Systems. 1.2
Neural Computation and Analog Integrated Circuits. 2 Visual Motion
Perception. 2.1 Image Brightness. 2.2 Correspondence Problem. 2.3 Optical
Flow. 2.4 Matching Models. 2.4.1 Explicit matching. 2.4.2 Implicit
matching. 2.5 FlowModels. 2.5.1 Global motion. 2.5.2 Local motion. 2.5.3
Perceptual bias. 2.6 Outline for a Visual Motion Perception System. 2.7
Review of aVLSI Implementations. 3 Optimization Networks. 3.1
AssociativeMemory and Optimization. 3.2 Constraint Satisfaction Problems.
3.3 Winner-takes-all Networks. 3.3.1 Network architecture. 3.3.2 Global
convergence and gain. 3.4 Resistive Network. 4 Visual Motion Perception
Networks. 4.1 Model for Optical Flow Estimation. 4.1.1 Well-posed
optimization problem. 4.1.2 Mechanical equivalent. 4.1.3 Smoothness and
sparse data. 4.1.4 Probabilistic formulation. 4.2 Network Architecture.
4.2.1 Non-stationary optimization. 4.2.2 Network conductances. 4.3
Simulation Results for Natural Image Sequences. 4.4 Passive Non-linear
Network Conductances. 4.5 Extended Recurrent Network Architectures. 4.5.1
Motion segmentation. 4.5.2 Attention and motion selection. 4.6 Remarks. 5
Analog VLSI Implementation. 5.1 Implementation Substrate. 5.2
Phototransduction. 5.2.1 Logarithmic adaptive photoreceptor. 5.2.2 Robust
brightness constancy constraint. 5.3 Extraction of the Spatio-temporal
Brightness Gradients. 5.3.1 Temporal derivative circuits. 5.3.2 Spatial
sampling. 5.4 Single Optical Flow Unit. 5.4.1 Wide-linear-range multiplier.
5.4.2 Effective bias conductance. 5.4.3 Implementation of the smoothness
constraint. 5.5 Layout. 6 Smooth Optical Flow Chip. 6.1 Response
Characteristics. 6.1.1 Speed tuning. 6.1.2 Contrast dependence. 6.1.3
Spatial frequency tuning. 6.1.4 Orientation tuning. 6.2
Intersection-of-constraints Solution. 6.3 Flow Field Estimation. 6.4
DeviceMismatch. 6.4.1 Gradient offsets. 6.4.2 Variations across the array.
6.5 Processing Speed. 6.6 Applications. 6.6.1 Sensor modules for robotic
applications. 6.6.2 Human-machine interface. 7 Extended Network
Implementations. 7.1 Motion Segmentation Chip. 7.1.1 Schematics of the
motion segmentation pixel. 7.1.2 Experiments and results. 7.2 Motion
Selection Chip. 7.2.1 Pixel schematics. 7.2.2 Non-linear diffusion length.
7.2.3 Experiments and results. 8 Comparison to Human Motion Vision. 8.1
Human vs. Chip Perception. 8.1.1 Contrast-dependent speed perception. 8.1.2
Bias on perceived direction of motion. 8.1.3 Perceptual dynamics. 8.2
Computational Architecture. 8.3 Remarks. Appendix. A Variational Calculus.
B Simulation Methods. C Transistors and Basic Circuits. D Process
Parameters and Chips Specifications. References. Index.

Rezensionen

"...provides unconventional and fresh perspectives on how to understand perception and build simple artificial perceptual systems using VLSI circuits." ( The Neurimorphic Engineer, March 2007